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# YOLO 🚀 by Ultralytics, GPL-3.0 license
# Default training settings and hyperparameters for medium-augmentation COCO training
# Task and Mode
task: "classify" # choices=['detect', 'segment', 'classify', 'init'] # init is a special case
mode: "train" # choice=['train', 'val', 'predict']
# Train settings -------------------------------------------------------------------------------------------------------
model: null # i.e. yolov5s.pt, yolo.yaml
data: null # i.e. coco128.yaml
epochs: 100
batch_size: 16
imgsz: 640
nosave: False
cache: False # True/ram, disk or False
device: '' # cuda device, i.e. 0 or 0,1,2,3 or cpu
workers: 8
project: 'runs/train'
name: 'exp'
exist_ok: False
pretrained: False
optimizer: 'SGD' # choices=['SGD', 'Adam', 'AdamW', 'RMSProp']
verbose: False
seed: 0
deterministic: True
local_rank: -1
single_cls: False # train multi-class data as single-class
image_weights: False # use weighted image selection for training
rect: False # support rectangular training
cos_lr: False # use cosine LR scheduler
close_mosaic: 10 # disable mosaic for final 10 epochs
# Segmentation
overlap_mask: True # masks overlap
mask_ratio: 4 # mask downsample ratio
# Classification
dropout: False # use dropout
resume: False
# Val/Test settings ----------------------------------------------------------------------------------------------------
noval: False
save_json: False
save_hybrid: False
conf_thres: 0.001
iou_thres: 0.7
max_det: 300
half: True
dnn: False # use OpenCV DNN for ONNX inference
plots: True
# Prediction settings:
source: "ultralytics/assets/"
view_img: False
save_txt: False
save_conf: False
save_crop: False
hide_labels: False # hide labels
hide_conf: False
vid_stride: 1 # video frame-rate stride
line_thickness: 3 # bounding box thickness (pixels)
update: False # Update all models
visualize: False
augment: False
agnostic_nms: False # class-agnostic NMS
retina_masks: False
# Hyperparameters ------------------------------------------------------------------------------------------------------
lr0: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3)
lrf: 0.01 # final OneCycleLR learning rate (lr0 * lrf)
momentum: 0.937 # SGD momentum/Adam beta1
weight_decay: 0.0005 # optimizer weight decay 5e-4
warmup_epochs: 3.0 # warmup epochs (fractions ok)
warmup_momentum: 0.8 # warmup initial momentum
warmup_bias_lr: 0.1 # warmup initial bias lr
box: 7.5 # box loss gain
cls: 0.5 # cls loss gain (scale with pixels)
dfl: 1.5 # dfl loss gain
fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)
label_smoothing: 0.0
nbs: 64 # nominal batch size
hsv_h: 0.015 # image HSV-Hue augmentation (fraction)
hsv_s: 0.7 # image HSV-Saturation augmentation (fraction)
hsv_v: 0.4 # image HSV-Value augmentation (fraction)
degrees: 0.0 # image rotation (+/- deg)
translate: 0.1 # image translation (+/- fraction)
scale: 0.5 # image scale (+/- gain)
shear: 0.0 # image shear (+/- deg)
perspective: 0.0 # image perspective (+/- fraction), range 0-0.001
flipud: 0.0 # image flip up-down (probability)
fliplr: 0.5 # image flip left-right (probability)
mosaic: 1.0 # image mosaic (probability)
mixup: 0.0 # image mixup (probability)
copy_paste: 0.0 # segment copy-paste (probability)
# For debugging. Don't change
v5loader: True
# Hydra configs --------------------------------------------------------------------------------------------------------
hydra:
output_subdir: null # disable hydra directory creation
run:
dir: .